Thermal and Multispectral Remote Sensing for the Detection and Analysis of Archaeologically Induced Crop Stress at a UK Site

Katherine James,Caroline J Nichol,Tom Wade,Jack Gillespie,Andrew Gray,Simon Gibson Poole,Dave Cowley

doi:10.3390/drones4040061

Katherine James, Caroline J Nichol + Show 5 more

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https://doi.org/10.3390/drones4040061

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Journal: Drones	Publication Date: Sep 24, 2020
Citations: 18	License type: CC BY 4.0

Affiliation: University of Edinburgh, Scotland's Rural College

Abstract

In intensively cultivated landscapes, many archaeological remains are buried under the ploughed soil, and detection depends on crop proxies that express subsurface features. Traditionally these proxies have been documented in visible light as contrasting areas of crop development commonly known as cropmarks. However, it is recognised that reliance on the visible electromagnetic spectrum has inherent limitations on what can be documented, and multispectral and thermal sensors offer the potential to greatly improve our ability to detect buried archaeological features in agricultural fields. The need for this is pressing, as ongoing agricultural practices place many subsurface archaeological features increasingly under threat of destruction. The effective deployment of multispectral and thermal sensors, however, requires a better understanding of when they may be most effective in documenting archaeologically induced responses. This paper presents the first known use of the FLIR Vue Pro-R thermal imager and Red Edge-M for exploring crop response to archaeological features from two UAV surveys flown in May and June 2019 over a known archaeological site. These surveys provided multispectral imagery, which was used to create vegetation index (VI) maps, and thermal maps to assess their effectiveness in detecting crop responses in the temperate Scottish climate. These were visually and statistically analysed using a Mann Whitney test to compare temperature and reflectance values. While the study was compromised by unusually damp conditions which reduced the potential for cropmarking, the VIs (e.g., Normalised Difference Vegetation Index, NDVI) did show potential to detect general crop stress across the study site when they were statistically analysed. This demonstrates the need for further research using multitemporal data collection across case study sites to better understand the interactions of crop responses and sensors, and so define appropriate conditions for large-area data collection. Such a case study-led multitemporal survey approach is an ideal application for UAV-based documentation, especially when “perfect” conditions cannot be guaranteed.

Highlights

Remote sensing is a long-established non-intrusive method of archaeological survey and documentation, making significant contributions to site discovery and archaeological understanding [1,2].In agricultural landscapes, this work relies heavily on observation of variegation and contrast in crops to reveal otherwise buried archaeological sites
All vegetation index (VI) maps for the 24 May survey (Figure 4) and that undertaken on 26 June (Figure 5) were visually analysed for evidence indicative of buried archaeological features
This can be seen by a change in mean reflectance in the feature region across the two surveys, e.g., normalised difference vegetation index (NDVI) increases from 0.573 to 0.742 in the feature region (Table 3), showing that the vegetation has improved in vigour by 26 June

Summary

Introduction

Remote sensing is a long-established non-intrusive method of archaeological survey and documentation, making significant contributions to site discovery and archaeological understanding [1,2].In agricultural landscapes, this work relies heavily on observation of variegation and contrast in crops to reveal otherwise buried archaeological sites. While most cropmarks have traditionally been observed in the visible electromagnetic spectrum, there is increasing interest in new technologies that collect information outside the visible range, such as multispectral and thermal imagers [8,9,10] This is driven both by technological developments and archaeological imperatives. Whilst multispectral and hyperspectral imaging has been shown to have great advantages in crop stress detection [14,15], there are mixed results using thermal imagery as a detection method This highlights the need for further exploration [10,16,17,18], especially to better understand when large area data collections are most likely to produce good returns. The study reported on here is based around an MSc student dissertation that forms part of a research project, between Historic Environment Scotland (HES)

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